Liu Jia, Villanueva Paul, Choi Jinlyung, Gunturu Santosh, Ouyang Yang, Tiemann Lisa K, Cole James R, Glanville Kathryn R, Hall Steven J, McDaniel Marshall D, Lee Jaejin, Howe Adina
Department of Agricultural and Biosystems Engineering, Iowa State Universitygrid.34421.30, Ames, Iowa, USA.
Bioinformatics and Computational Biology Department, Iowa State University, Ames, Iowa, USA.
mSystems. 2021 Oct 26;6(5):e0020121. doi: 10.1128/mSystems.00201-21. Epub 2021 Sep 21.
Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (A) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these -AOB primers can cover 94% of the A-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably. Amplification-based gene characterization allows for sensitive and specific quantification of functional genes. There is often a large diversity of genes represented for functional gene groups, and multiple primers may be necessary to target associated genes. Current primer design tools are limited to designing primers for only a few genes of interest. MetaFunPrimer allows for high-throughput primer design for various genes of interest and also allows for ranking gene targets by their presence and abundance in environmental data sets. Primers designed by this tool improve the characterization and quantification of functional genes in broad gene amplification platforms and can be powerful with high-throughput qPCR approaches.
属于同一功能组的基因可能包含众多且可变的基因序列,这使得表征和定量变得困难。因此,需要高通量设计工具来同时创建引物,以改进目标基因的定量。我们开发了MetaFunPrimer,这是一种生物信息学流程,用于为众多感兴趣的基因设计引物。该工具还能够根据基因在用户定义的参考序列(如特定环境的宏基因组)中的存在情况进行排名,从而对基因靶点进行优先级排序。给定感兴趣的基因靶点的蛋白质和核苷酸序列输入以及一组伴随的参考宏基因组或基因组,MetaFunPrimer会为排名靠前的感兴趣基因生成引物。为了证明MetaFunPrimer的用法和优势,我们设计了总共78对引物,以靶向1550个公开可用土壤宏基因组中观察到的氨氧化细菌(AOB)的氨单加氧酶亚基A(A)基因。我们通过计算证明,与先前发表的引物估计的49%覆盖率相比,这些AOB引物可以覆盖1550个土壤宏基因组中观察到的94%的A - AOB基因。最后,我们在使用长期施氮或未施氮土壤的培养实验中验证了这些引物组的实用性。高通量定量PCR(qPCR)结果和统计分析表明,两种土壤之间的相对定量模式存在显著差异,随后的绝对定量也证实,六种选定引物对所枚举的目标基因在施氮土壤中明显更为丰富。这种新工具为微生物生态学家提供了一种新方法,能够快速且经济地评估功能基因丰度和相关微生物群落动态。基于扩增的基因表征允许对功能基因进行灵敏且特异的定量。功能基因组通常代表着大量不同的基因,可能需要多个引物来靶向相关基因。当前的引物设计工具仅限于为少数感兴趣的基因设计引物。MetaFunPrimer允许对各种感兴趣的基因进行高通量引物设计,还能根据基因在环境数据集中的存在情况和丰度对基因靶点进行排名。通过该工具设计的引物改进了在广泛的基因扩增平台中功能基因的表征和定量,并且在高通量qPCR方法中可能会很强大。